About: Functional data analysis

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Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function. The physical continuum over which these functions are defined is often time, but may also be spatial location, wavelength, probability, etc. Intrinsically, functional data are infinite dimensional. The high intrinsic dimensionality of these data brings challenges for theory as well as computation, where these challenges vary with how the functional data were sampled. However, the high or infinite dimensional structure of the data is a rich source of information and there are many interesting challenges

Attributes	Values
rdf:type	organisation
rdfs:label	Functional data analysis (en)
rdfs:comment	Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function. The physical continuum over which these functions are defined is often time, but may also be spatial location, wavelength, probability, etc. Intrinsically, functional data are infinite dimensional. The high intrinsic dimensionality of these data brings challenges for theory as well as computation, where these challenges vary with how the functional data were sampled. However, the high or infinite dimensional structure of the data is a rich source of information and there are many interesting challenges (en)
foaf:depiction
dcterms:subject	Statistical analysis Statistical data types
Wikipage page ID	2141368 (xsd:integer)
Wikipage revision ID	1118304927 (xsd:integer)
Link from a Wikipage to another Wikipage	Python (programming language) Mercer's theorem Variance function Bernard Silverman Regression analysis Pettis integral Curse of dimensionality Variance Dynamic time warping Statistical analysis Generalized functional linear model Generalized linear model Mixture model Semiparametric regression Eigenvectors Functional regression Conditional expectation Linear operator Lp space Bochner integral Statistics Stochastic processes Compact operator on Hilbert space Functional principal component analysis Spline (mathematics) Additive model Statistical data types K-means clustering Linear predictor function Linear regression Link function Euclidean space Expected value Fourier series Diffeomorphism Dimensionality reduction Kolmogorov continuity theorem Speech recognition Hilbert space James O. Ramsay Covariance operator Tensor product Karhunen–Loève theorem Hierarchical clustering Modes of variation Spectral theorem ISBN (identifier) Inner product space R (programming language) Square-integrable function Polynomial regression Stochastic process Functional principal components analysis Eigenvalues Karhunen–Loève expansion Sobolov space dbr:Special:BookSources/978-1-4614-3654-6
Link from a Wikipage to an external page	https://rdrr.io/cran/fda/man/growth.html%23heading-0 https://www.marketwatch.com/investing/stock/live https://www.rdocumentation.org/packages/classiFunc/versions/0.1.1 https://doi.org/10.1146/annurev-statistics-010814-020413 https://doi.org/10.1146/annurev-statistics-041715-033624 https://github.com/GAA-UAM/scikit-fda https://cran.r-project.org/web/packages/FDboost/index.html https://cran.r-project.org/web/packages/dtw/index.html https://cran.r-project.org/web/packages/fda.usc/index.html https://cran.r-project.org/web/packages/fda/index.html https://cran.r-project.org/web/packages/fdapace/index.html https://cran.r-project.org/web/packages/fdasrvf/index.html https://cran.r-project.org/web/packages/refund/index.html
sameAs	Functional data analysis Functional data analysis Functional data analysis Functional data analysis
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has abstract	Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function. The physical continuum over which these functions are defined is often time, but may also be spatial location, wavelength, probability, etc. Intrinsically, functional data are infinite dimensional. The high intrinsic dimensionality of these data brings challenges for theory as well as computation, where these challenges vary with how the functional data were sampled. However, the high or infinite dimensional structure of the data is a rich source of information and there are many interesting challenges for research and data analysis. (en)
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page length (characters) of wiki page	47852 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Functional_data_analysis
is Link from a Wikipage to another Wikipage of	FDA (disambiguation) Variance function Bernard Silverman Victor Panaretos Dynamic time warping Jane-Ling Wang

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